Bio-Inspired Evolutionary and Swarm Optimization Algorithms
Lidia Ghosh, Antara Ghosh · 2025
This chapter provides a comprehensive overview of bio-inspired optimization algorithms, focusing on evolutionary and swarm intelligence techniques that draw on natural processes. By mimicking behaviors observed in biological entities—such as the survival strategies of animal groups, evolutionary adaptations, and swarm dynamics—these algorithms offer robust solutions for complex optimization problems across various domains. Core algorithms discussed include Genetic Algorithms (GAs), Differential Evolution (DE), Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and others, each representing unique strategies to balance exploration and exploitation within the search space. Additionally, the chapter explores recent applications of these algorithms in fields such as engineering, healthcare, and finance, highlighting their adaptability and efficiency in solving real-world optimization challenges.